
Codebook for data used in "Facial Recognition Technology and Voter Turnout"
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Variables in each datafile

kompally.csv:
-polling station: polling station number
-ward: ward number
-female_eligible: number of female voters assigned to station
-female_eligible: number of female voters assigned to station
-total_eligible: number of total voters assigned to station (variable for other gender is not used in analysis so had to be removed from the data)
-male_voted: number of males who voted
-female_voted: number of females who voted
-total_voted: number of females who voted(variable for other gender who voted is not used in analysis so had to be removed from the data)
-turnout: voter turnout for election
-male_turnout: male voter turnout for election
-female_turnout: female voter turnout for election
-polling_location: polling station location
-facial_recognition: indicator for whether the station used facial recognition technology
-n_party: number of parties competing in the election
-turnout_ge: turnout in this station for the 2019 general elections
-any_res: indicator for if there was any reservations in this ward
-women_res: indicator for if there was a gender reservation in this ward
-scst_res: indicator for if there was a schedule caste or tribe reservation in this ward
-bc_res: indicator for if there was an other backward caste reservation in this ward
-pfemale: percent of women assigned to the station
-percentmuslim_method1: estimated percent of Muslims assigned to the station using method outlined in Appendix
-percentmuslim_method2: estimated percent of Muslims assigned to the station using method outlined in Appendix

kompally_ward.csv:
-ward: ward number
-frt_binary: if there was any FRT in either of the two polling stations in the ward
-BJP: BJP party vote share percentage
-INC: INC party vote share percentage
-TRS: TRS party vote share percentage

kompally_candidate.csv:
-ward: ward number
-position: position of party
-party: party abbreviation
-percent_vote: vote share for party
-diff_win_second: margin between winner and runner-up

kompally_general_election.csv:
-polling_location: polling station location
-eligible_total: number of total voters assigned to station
-inc_vote_reddy: number of votes for INC candidate
-trs_vote_marri: number of votes for TRS candidate
-bjp_vote_naraparju: number of vote for BJP candidate
-voted_total: total votes casted
-ward_2020: 2020 ward linked to this 2019 polling location

frt_worldwide.csv:
-code: country three-letter iso code
-frt_status: information on country's use of FRT

frt_india.csv:
-state: state name
-frt_systems: number of FRT systems in state

census_select_districts.csv:
-District: district number
-Level: level of administrative unit
-TRU: type of area - total, urban, rural
-TOT_M: male population
-TOT_F: female population
-P_SC: scheduled caste population
-TOT_P: total population
-P_ST: scheduled tribe population
-M_LIT: male literate population
-F_LIT: female literate population
-TOT_WORK_P: total working population
-MAIN_AL_P: total agricultural population
-Name: name of area

frt_google_trends.csv:
-date: date
-frt: google trends search index for "facial recognition"

india_state.shp:
ST_NM: state name
geometry: GIS polygon for state

telangana.shp:
NAME_3: sub-district name
geometry: GIS polygon for sub-district










